{"id":477479,"date":"2023-08-09T09:15:39","date_gmt":"2023-08-09T09:15:39","guid":{"rendered":""},"modified":"2023-09-05T11:14:48","modified_gmt":"2023-09-05T11:14:48","slug":"hosted-jupyter","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/cn\/wiki\/hosted-jupyter\/","title":{"rendered":"\u6258\u7ba1 Jupyter"},"content":{"rendered":"

Hosted Jupyter \u662f\u4e00\u79cd\u521b\u65b0\u4e14\u5f3a\u5927\u7684\u5de5\u5177\uff0c\u5b83\u5f7b\u5e95\u6539\u53d8\u4e86\u6570\u636e\u79d1\u5b66\u548c\u534f\u4f5c\u7814\u7a76\u7684\u4e16\u754c\u3002 Jupyter \u6700\u521d\u662f\u4f5c\u4e3a\u4e00\u4e2a\u5f00\u6e90\u9879\u76ee\u5f00\u53d1\u7684\uff0c\u73b0\u5df2\u6210\u4e3a\u4ea4\u4e92\u5f0f\u8ba1\u7b97\u3001\u6570\u636e\u5206\u6790\u548c\u53ef\u89c6\u5316\u7684\u5e7f\u6cdb\u4f7f\u7528\u7684\u5e73\u53f0\u3002\u5728\u670d\u52a1\u5668\u4e0a\u6258\u7ba1 Jupyter \u5141\u8bb8\u591a\u4e2a\u7528\u6237\u540c\u65f6\u8bbf\u95ee\u7b14\u8bb0\u672c\u5e76\u5728\u7b14\u8bb0\u672c\u4e0a\u8fdb\u884c\u534f\u4f5c\uff0c\u8fd9\u4f7f\u5176\u6210\u4e3a\u5bfb\u6c42\u4fc3\u8fdb\u56e2\u961f\u5408\u4f5c\u548c\u7b80\u5316\u6570\u636e\u9a71\u52a8\u5de5\u4f5c\u6d41\u7a0b\u7684\u4f01\u4e1a\u3001\u7814\u7a76\u4eba\u5458\u548c\u5b66\u672f\u673a\u6784\u7684\u7406\u60f3\u89e3\u51b3\u65b9\u6848\u3002<\/p>\n

Hosted Jupyter \u7684\u8d77\u6e90\u5386\u53f2\u4ee5\u53ca\u9996\u6b21\u63d0\u53ca<\/h2>\n

Hosted Jupyter \u7684\u6839\u6e90\u53ef\u4ee5\u8ffd\u6eaf\u5230 2014 \u5e74\uff0c\u5f53\u65f6\u8be5\u9879\u76ee\u7531 Fernando P\u00e9rez \u548c Brian Granger \u9886\u5bfc\u7684\u5f00\u53d1\u56e2\u961f\u9996\u6b21\u63a8\u51fa\u3002 \u201cJupyter\u201d\u8fd9\u4e2a\u540d\u5b57\u6765\u6e90\u4e8e\u4e09\u79cd\u6838\u5fc3\u7f16\u7a0b\u8bed\u8a00\uff1aJulia\u3001Python\u548cR\u7684\u7ec4\u5408\uff0c\u6807\u5fd7\u7740\u5bf9\u8fd9\u4e9b\u8bed\u8a00\u7684\u521d\u6b65\u652f\u6301\u3002\u8be5\u9879\u76ee\u7684\u8d77\u6e90\u5728\u4e8eIPython\uff0c\u4e00\u4e2aPython\u7684\u4ea4\u4e92\u5f0f\u8ba1\u7b97\u73af\u5883\uff0c\u6700\u7ec8\u6f14\u53d8\u6210\u66f4\u5e7f\u6cdb\u7684Jupyter\u751f\u6001\u7cfb\u7edf\u3002<\/p>\n

\u6709\u5173\u6258\u7ba1 Jupyter \u7684\u8be6\u7ec6\u4fe1\u606f<\/h2>\n

\u6258\u7ba1 Jupyter \u672c\u8d28\u4e0a\u662f\u4e00\u4e2a\u57fa\u4e8e Web \u7684\u754c\u9762\uff0c\u5141\u8bb8\u7528\u6237\u521b\u5efa\u548c\u5171\u4eab\u6587\u6863\uff08\u79f0\u4e3a\u201c\u7b14\u8bb0\u672c\u201d\uff09\uff0c\u5176\u4e2d\u5305\u542b\u5b9e\u65f6\u4ee3\u7801\u3001\u53ef\u89c6\u5316\u548c\u89e3\u91ca\u6027\u6587\u672c\u3002\u8be5\u5e73\u53f0\u652f\u6301\u591a\u79cd\u7f16\u7a0b\u8bed\u8a00\uff0c\u5305\u62ecPython\u3001R\u3001Julia\u7b49\uff0c\u4f7f\u5176\u6210\u4e3a\u8de8\u9886\u57df\u6570\u636e\u5206\u6790\u548c\u79d1\u5b66\u8ba1\u7b97\u7684\u591a\u529f\u80fd\u9009\u62e9\u3002<\/p>\n

\u6258\u7ba1 Jupyter \u7684\u5173\u952e\u7ec4\u4ef6\u5305\u62ec\uff1a<\/p>\n

    \n
  1. \n

    \u6838\u5fc3<\/strong>\uff1a\u5728\u7b14\u8bb0\u672c\u5185\u6267\u884c\u4ee3\u7801\u7684\u5f15\u64ce\uff0c\u652f\u6301\u4e0d\u540c\u7684\u7f16\u7a0b\u8bed\u8a00\u3002\u6bcf\u4e2a\u7b14\u8bb0\u672c\u90fd\u8fd0\u884c\u5728\u5355\u72ec\u7684\u5185\u6838\u4e0a\uff0c\u4f7f\u7528\u6237\u80fd\u591f\u5728\u8bed\u8a00\u4e4b\u95f4\u65e0\u7f1d\u5207\u6362\u3002<\/p>\n<\/li>\n

  2. \n

    \u7b14\u8bb0\u672c\u6587\u6863<\/strong>\uff1a\u57fa\u4e8e JSON \u7684\u6587\u4ef6\uff0c\u7528\u4e8e\u5b58\u50a8\u7b14\u8bb0\u672c\u7684\u5185\u5bb9\uff0c\u4f8b\u5982\u4ee3\u7801\u3001\u6587\u672c\u548c\u8f93\u51fa\u3002\u7b14\u8bb0\u672c\u53ef\u4ee5\u5171\u4eab\u3001\u7248\u672c\u63a7\u5236\u5e76\u7528\u4f5c\u4ea4\u4e92\u5f0f\u6559\u7a0b\u3002<\/p>\n<\/li>\n

  3. \n

    \u524d\u7aef<\/strong>\uff1a\u5728 Web \u6d4f\u89c8\u5668\u4e2d\u8fd0\u884c\u7684\u7528\u6237\u754c\u9762\uff0c\u53ef\u5b9e\u73b0\u4e0e\u7b14\u8bb0\u672c\u7684\u4ea4\u4e92\u4ee5\u53ca\u4ee3\u7801\u8f93\u51fa\u7684\u53ef\u89c6\u5316\u3002<\/p>\n<\/li>\n

  4. \n

    \u4e2d\u95f4\u4ef6<\/strong>\uff1a\u5904\u7406\u524d\u7aef\u548c\u5185\u6838\u4e4b\u95f4\u7684\u901a\u4fe1\uff0c\u4fc3\u8fdb\u4ee3\u7801\u7684\u6267\u884c\u5e76\u6355\u83b7\u7ed3\u679c\u3002<\/p>\n<\/li>\n<\/ol>\n

    Hosted Jupyter \u7684\u5185\u90e8\u7ed3\u6784\uff1aHosted Jupyter \u7684\u5de5\u4f5c\u539f\u7406<\/h2>\n

    \u5f53\u7528\u6237\u8bbf\u95ee\u6258\u7ba1 Jupyter \u5b9e\u4f8b\u65f6\uff0cWeb \u6d4f\u89c8\u5668\u5145\u5f53\u524d\u7aef\uff0c\u63d0\u4f9b\u7528\u4e8e\u521b\u5efa\u548c\u7f16\u8f91\u7b14\u8bb0\u672c\u7684\u4ea4\u4e92\u5f0f\u754c\u9762\u3002\u7b14\u8bb0\u672c\u6587\u6863\u5b58\u50a8\u5728\u670d\u52a1\u5668\u4e0a\uff0c\u5185\u6838\u5904\u7406\u7528\u6237\u8f93\u5165\u7684\u4ee3\u7801\uff0c\u751f\u6210\u5305\u62ec\u6587\u672c\u3001\u56fe\u50cf\u548c\u4ea4\u4e92\u5f0f\u53ef\u89c6\u5316\u7684\u8f93\u51fa\u3002<\/p>\n

    Hosted Jupyter \u5185\u7684\u901a\u4fe1\u6d41\u7a0b\u53ef\u603b\u7ed3\u5982\u4e0b\uff1a<\/p>\n

      \n
    1. \u524d\u7aef\u5c06\u4ee3\u7801\u8f93\u5165\u53d1\u9001\u5230\u5185\u6838\u4ee5\u4f9b\u6267\u884c\u3002<\/li>\n
    2. \u5185\u6838\u5904\u7406\u4ee3\u7801\u5e76\u751f\u6210\u8f93\u51fa\u3002<\/li>\n
    3. \u8f93\u51fa\u88ab\u53d1\u9001\u56de\u524d\u7aef\uff0c\u5e76\u5728\u524d\u7aef\u663e\u793a\u7ed9\u7528\u6237\u3002<\/li>\n<\/ol>\n

      Hosted Jupyter \u7684\u8fd9\u79cd\u4ea4\u4e92\u5f0f\u548c\u52a8\u6001\u7279\u6027\u4fc3\u8fdb\u4e86\u534f\u4f5c\u5e76\u589e\u5f3a\u4e86\u6570\u636e\u5206\u6790\u548c\u7814\u7a76\u7684\u53ef\u91cd\u590d\u6027\u3002<\/p>\n

      Hosted Jupyter\u5173\u952e\u7279\u6027\u5206\u6790<\/h2>\n

      Hosted Jupyter \u63d0\u4f9b\u4e86\u5e7f\u6cdb\u7684\u529f\u80fd\uff0c\u4f7f\u5176\u6210\u4e3a\u6570\u636e\u79d1\u5b66\u5bb6\u3001\u7814\u7a76\u4eba\u5458\u548c\u6559\u80b2\u5de5\u4f5c\u8005\u4e0d\u53ef\u6216\u7f3a\u7684\u5de5\u5177\uff1a<\/p>\n

        \n
      1. \n

        \u4ea4\u4e92\u5f0f\u8ba1\u7b97<\/strong>\uff1a\u6258\u7ba1 Jupyter \u5141\u8bb8\u7528\u6237\u5b9e\u65f6\u6267\u884c\u4ee3\u7801\uff0c\u4ece\u800c\u66f4\u8f7b\u677e\u5730\u63a2\u7d22\u6570\u636e\u3001\u8bd5\u9a8c\u7b97\u6cd5\u5e76\u5373\u65f6\u53ef\u89c6\u5316\u7ed3\u679c\u3002<\/p>\n<\/li>\n

      2. \n

        \u53ef\u89c6\u5316<\/strong>\uff1a\u901a\u8fc7\u5bf9\u5bcc\u5a92\u4f53\u8f93\u51fa\u7684\u652f\u6301\uff0c\u6258\u7ba1 Jupyter \u4f7f\u7528\u6237\u80fd\u591f\u521b\u5efa\u5f15\u4eba\u5165\u80dc\u7684\u53ef\u89c6\u5316\u6548\u679c\uff0c\u4ece\u800c\u589e\u5f3a\u6570\u636e\u7406\u89e3\u548c\u6c9f\u901a\u3002<\/p>\n<\/li>\n

      3. \n

        \u4ee3\u7801\u5171\u4eab\u4e0e\u534f\u4f5c<\/strong>\uff1a\u901a\u8fc7\u5728\u670d\u52a1\u5668\u4e0a\u6258\u7ba1 Jupyter\uff0c\u591a\u4e2a\u7528\u6237\u53ef\u4ee5\u540c\u65f6\u5728\u540c\u4e00\u4e2a\u7b14\u8bb0\u672c\u4e0a\u8fdb\u884c\u534f\u4f5c\uff0c\u4f7f\u5176\u6210\u4e3a\u56e2\u961f\u9879\u76ee\u548c\u4ea4\u4e92\u5f0f\u7814\u8ba8\u4f1a\u7684\u7406\u60f3\u5e73\u53f0\u3002<\/p>\n<\/li>\n

      4. \n

        \u6587\u6863\u548c\u6f14\u793a<\/strong>\uff1aJupyter \u7b14\u8bb0\u672c\u4f5c\u4e3a\u72ec\u7acb\u6587\u6863\uff0c\u53ef\u4ee5\u5305\u542b\u4ee3\u7801\u548c\u53d9\u8ff0\u6587\u672c\uff0c\u4fc3\u8fdb\u7814\u7a76\u7ed3\u679c\u7684\u518d\u73b0\u548c\u5171\u4eab\u3002<\/p>\n<\/li>\n

      5. \n

        \u53ef\u6269\u5c55\u6027<\/strong>\uff1aJupyter \u751f\u6001\u7cfb\u7edf\u5141\u8bb8\u96c6\u6210\u5404\u79cd\u6269\u5c55\u548c\u5c0f\u90e8\u4ef6\uff0c\u6839\u636e\u7279\u5b9a\u9700\u6c42\u589e\u5f3a\u529f\u80fd\u548c\u5b9a\u5236\u3002<\/p>\n<\/li>\n

      6. \n

        \u652f\u6301\u591a\u79cd\u7f16\u7a0b\u8bed\u8a00<\/strong>\uff1a\u6258\u7ba1 Jupyter \u5bf9\u5404\u79cd\u7f16\u7a0b\u8bed\u8a00\u7684\u652f\u6301\u786e\u4fdd\u7528\u6237\u53ef\u4ee5\u4f7f\u7528\u4ed6\u4eec\u6700\u719f\u6089\u7684\u5de5\u5177\u548c\u5e93\u3002<\/p>\n<\/li>\n<\/ol>\n

        \u6258\u7ba1 Jupyter \u7684\u7c7b\u578b<\/h2>\n

        \u6258\u7ba1 Jupyter \u6709\u4e0d\u540c\u7684\u98ce\u683c\uff0c\u6bcf\u79cd\u98ce\u683c\u90fd\u6ee1\u8db3\u7279\u5b9a\u7684\u7528\u4f8b\u548c\u8981\u6c42\u3002\u6258\u7ba1 Jupyter \u7684\u4e00\u4e9b\u5e38\u89c1\u7c7b\u578b\u662f\uff1a<\/p>\n\n\n\n\n\n\n\n
        \u7c7b\u578b<\/th>\n\u63cf\u8ff0<\/th>\n<\/tr>\n<\/thead>\n
        \u516c\u5171\u6258\u7ba1<\/td>\n\u57fa\u4e8e Web \u7684\u5e73\u53f0\uff0c\u63d0\u4f9b\u6258\u7ba1 Jupyter \u5b9e\u4f8b\u4f9b\u514d\u8d39\u516c\u4f17\u4f7f\u7528\u3002<\/td>\n<\/tr>\n
        \u79c1\u4eba\u6258\u7ba1<\/td>\n\u5b9a\u5236\u7684\u6258\u7ba1 Jupyter \u89e3\u51b3\u65b9\u6848\u90e8\u7f72\u5728\u79c1\u6709\u670d\u52a1\u5668\u4e0a\uff08\u901a\u5e38\u5728\u7ec4\u7ec7\u5185\uff09\u3002<\/td>\n<\/tr>\n
        \u57fa\u4e8e\u4e91\u7684\u6258\u7ba1<\/td>\nJupyter \u7b14\u8bb0\u672c\u6258\u7ba1\u5728\u4e91\u5e73\u53f0\u4e0a\uff0c\u5141\u8bb8\u7528\u6237\u4ece\u4efb\u4f55\u5730\u65b9\u8bbf\u95ee\u5b83\u4eec\u3002<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        Hosted Jupyter\u7684\u4f7f\u7528\u65b9\u6cd5\u3001\u4f7f\u7528\u8fc7\u7a0b\u4e2d\u9047\u5230\u7684\u95ee\u9898\u4ee5\u53ca\u89e3\u51b3\u65b9\u6848<\/h2>\n

        \u6258\u7ba1 Jupyter \u5728\u5404\u4e2a\u9886\u57df\u5177\u6709\u591a\u79cd\u7528\u9014\u3002\u4e00\u4e9b\u5e38\u89c1\u7684\u7528\u4f8b\u5305\u62ec\uff1a<\/p>\n

          \n
        1. \n

          \u6570\u636e\u5206\u6790<\/strong>\uff1a\u6570\u636e\u79d1\u5b66\u5bb6\u4f7f\u7528\u6258\u7ba1 Jupyter \u6765\u5206\u6790\u548c\u53ef\u89c6\u5316\u6570\u636e\u96c6\u3001\u6267\u884c\u7edf\u8ba1\u5206\u6790\u4ee5\u53ca\u6784\u5efa\u673a\u5668\u5b66\u4e60\u6a21\u578b\u3002<\/p>\n<\/li>\n

        2. \n

          \u6559\u80b2\u4e0e\u7814\u7a76<\/strong>\uff1a\u5b66\u8005\u548c\u7814\u7a76\u4eba\u5458\u4f7f\u7528 Hosted Jupyter \u8fdb\u884c\u4ea4\u4e92\u5f0f\u6559\u5b66\u3001\u5171\u4eab\u53ef\u91cd\u590d\u7684\u7814\u7a76\u4ee5\u53ca\u8fdb\u884c\u5b9e\u9a8c\u3002<\/p>\n<\/li>\n

        3. \n

          \u6570\u636e\u53ef\u89c6\u5316<\/strong>\uff1a\u8be5\u5e73\u53f0\u56e0\u521b\u5efa\u4ea4\u4e92\u5f0f\u4e14\u5177\u6709\u89c6\u89c9\u5438\u5f15\u529b\u7684\u6570\u636e\u53ef\u89c6\u5316\u4ee5\u4fc3\u8fdb\u6d1e\u5bdf\u800c\u5e7f\u53d7\u6b22\u8fce\u3002<\/p>\n<\/li>\n

        4. \n

          \u539f\u578b\u8bbe\u8ba1\u548c\u6d4b\u8bd5<\/strong>\uff1a\u5f00\u53d1\u4eba\u5458\u4f7f\u7528\u6258\u7ba1 Jupyter \u8fdb\u884c\u4ee3\u7801\u539f\u578b\u8bbe\u8ba1\u548c\u6d4b\u8bd5\u7b97\u6cd5\uff0c\u7136\u540e\u518d\u5c06\u5176\u96c6\u6210\u5230\u66f4\u5927\u7684\u5e94\u7528\u7a0b\u5e8f\u4e2d\u3002<\/p>\n<\/li>\n<\/ol>\n

          \u7528\u6237\u5728\u4f7f\u7528\u6258\u7ba1 Jupyter \u65f6\u53ef\u80fd\u9047\u5230\u7684\u6311\u6218\u5305\u62ec\uff1a<\/p>\n

            \n
          1. \n

            \u8d44\u6e90\u5bc6\u96c6\u578b<\/strong>\uff1a\u8fd0\u884c\u590d\u6742\u7684\u8ba1\u7b97\u6216\u5927\u578b\u6570\u636e\u96c6\u53ef\u80fd\u9700\u8981\u5927\u91cf\u7684\u670d\u52a1\u5668\u8d44\u6e90\u3002<\/p>\n<\/li>\n

          2. \n

            \u5b89\u5168\u95ee\u9898<\/strong>\uff1a\u5728\u5171\u4eab\u6258\u7ba1\u73af\u5883\u4e2d\uff0c\u7528\u6237\u5fc5\u987b\u8c28\u614e\u4fdd\u62a4\u654f\u611f\u6570\u636e\u548c\u4ee3\u7801\u3002<\/p>\n<\/li>\n

          3. \n

            \u7248\u672c\u51b2\u7a81<\/strong>\uff1a\u4e0e\u5176\u4ed6\u4eba\u534f\u4f5c\u65f6\uff0c\u7ba1\u7406\u4e0d\u540c\u7684\u8f6f\u4ef6\u5305\u7248\u672c\u53ef\u80fd\u5177\u6709\u6311\u6218\u6027\u3002<\/p>\n<\/li>\n<\/ol>\n

            \u8fd9\u4e9b\u95ee\u9898\u7684\u89e3\u51b3\u65b9\u6848\u5305\u62ec\uff1a<\/p>\n

              \n
            1. \n

              \u8d44\u6e90\u4f18\u5316<\/strong>\uff1a\u786e\u4fdd\u9ad8\u6548\u7684\u7f16\u7801\u5b9e\u8df5\u5e76\u4f7f\u7528\u57fa\u4e8e\u4e91\u7684\u89e3\u51b3\u65b9\u6848\u6839\u636e\u9700\u8981\u6269\u5c55\u8d44\u6e90\u3002<\/p>\n<\/li>\n

            2. \n

              \u5b89\u9632\u63aa\u65bd<\/strong>\uff1a\u5b9e\u65bd\u5f3a\u5927\u7684\u8eab\u4efd\u9a8c\u8bc1\u548c\u8bbf\u95ee\u63a7\u5236\u3001\u52a0\u5bc6\u654f\u611f\u6570\u636e\u4ee5\u53ca\u4f7f\u7528\u79c1\u6709\u6258\u7ba1\u5b9e\u4f8b\u3002<\/p>\n<\/li>\n

            3. \n

              \u96c6\u88c5\u7bb1\u5316<\/strong>\uff1a\u4f7f\u7528 Docker \u7b49\u5bb9\u5668\u5316\u6280\u672f\u6765\u4e00\u81f4\u5730\u7ba1\u7406\u5305\u7248\u672c\u548c\u4f9d\u8d56\u9879\u3002<\/p>\n<\/li>\n<\/ol>\n

              \u4e3b\u8981\u7279\u70b9\u53ca\u4e0e\u540c\u7c7b\u672f\u8bed\u7684\u5176\u4ed6\u6bd4\u8f83<\/h2>\n\n\n\n\n\n\n\n\n
              \u5b66\u671f<\/th>\n\u63cf\u8ff0<\/th>\n<\/tr>\n<\/thead>\n
              \u6258\u7ba1 Jupyter<\/td>\n\u57fa\u4e8e Web \u7684\u754c\u9762\uff0c\u7528\u4e8e\u521b\u5efa\u652f\u6301\u591a\u79cd\u7f16\u7a0b\u8bed\u8a00\u7684\u4ea4\u4e92\u5f0f\u7b14\u8bb0\u672c\u3002<\/td>\n<\/tr>\n
              Jupyter\u7b14\u8bb0\u672c<\/td>\n\u5305\u542b\u4ee3\u7801\u3001\u6587\u672c\u548c\u8f93\u51fa\u7684\u6587\u4ef6\uff0c\u4f7f\u7528 Jupyter \u754c\u9762\u521b\u5efa\u548c\u7f16\u8f91\u3002<\/td>\n<\/tr>\n
              Jupyter\u5b9e\u9a8c\u5ba4<\/td>\n\u6269\u5c55\u754c\u9762\uff0c\u63d0\u4f9b\u5177\u6709\u591a\u4e2a\u7a97\u683c\u7684\u66f4\u52a0\u96c6\u6210\u7684\u73af\u5883\u3002<\/td>\n<\/tr>\n
              \u8c37\u6b4c\u5408\u4f5c\u5b9e\u9a8c\u5ba4<\/td>\nGoogle \u63d0\u4f9b\u7684\u57fa\u4e8e\u4e91\u7684 Jupyter \u73af\u5883\uff0c\u63d0\u4f9b\u5bf9 GPU \u548c TPU \u7684\u514d\u8d39\u8bbf\u95ee\u3002<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

              \u4e0e\u6258\u7ba1 Jupyter \u76f8\u5173\u7684\u672a\u6765\u524d\u666f\u548c\u6280\u672f<\/h2>\n

              \u968f\u7740\u6570\u636e\u79d1\u5b66\u548c\u534f\u4f5c\u7814\u7a76\u7684\u4e0d\u65ad\u53d1\u5c55\uff0c\u6258\u7ba1 Jupyter \u53ef\u80fd\u4f1a\u53d6\u5f97\u91cd\u5927\u8fdb\u5c55\u3002\u4e00\u4e9b\u6f5c\u5728\u7684\u672a\u6765\u53d1\u5c55\u5305\u62ec\uff1a<\/p>\n

                \n
              1. \n

                \u63d0\u9ad8\u6027\u80fd<\/strong>\uff1a\u4e91\u57fa\u7840\u8bbe\u65bd\u548c\u8ba1\u7b97\u6280\u672f\u7684\u8fdb\u6b65\u5c06\u5b9e\u73b0\u66f4\u5feb\u3001\u8d44\u6e90\u6548\u7387\u66f4\u9ad8\u7684\u6258\u7ba1 Jupyter \u5b9e\u4f8b\u3002<\/p>\n<\/li>\n

              2. \n

                \u4eba\u5de5\u667a\u80fd\u7b14\u8bb0\u672c\u7535\u8111<\/strong>\uff1a\u96c6\u6210\u4eba\u5de5\u667a\u80fd\u52a9\u624b\uff0c\u4ee5\u5e2e\u52a9\u4ee3\u7801\u5efa\u8bae\u3001\u8c03\u8bd5\u548c\u81ea\u52a8\u53ef\u89c6\u5316\u3002<\/p>\n<\/li>\n

              3. \n

                \u52a0\u5f3a\u534f\u4f5c<\/strong>\uff1a\u4fc3\u8fdb\u5b9e\u65f6\u534f\u4f5c\u7f16\u8f91\u7684\u529f\u80fd\uff0c\u5b9e\u73b0\u8fdc\u7a0b\u7528\u6237\u4e4b\u95f4\u7684\u65e0\u7f1d\u56e2\u961f\u5408\u4f5c\u3002<\/p>\n<\/li>\n

              4. \n

                \u6269\u5c55\u7684\u8bed\u8a00\u652f\u6301<\/strong>\uff1a\u7ee7\u7eed\u96c6\u6210\u5176\u4ed6\u7f16\u7a0b\u8bed\u8a00\u548c\u5e93\uff0c\u4ee5\u6ee1\u8db3\u4e0d\u540c\u7684\u6570\u636e\u79d1\u5b66\u9700\u6c42\u3002<\/p>\n<\/li>\n<\/ol>\n

                \u5982\u4f55\u4f7f\u7528\u4ee3\u7406\u670d\u52a1\u5668\u6216\u5982\u4f55\u5c06\u4ee3\u7406\u670d\u52a1\u5668\u4e0e\u6258\u7ba1 Jupyter \u5173\u8054<\/h2>\n

                \u4ee3\u7406\u670d\u52a1\u5668\u5728\u589e\u5f3a\u6258\u7ba1 Jupyter \u5b9e\u4f8b\u7684\u5b89\u5168\u6027\u548c\u6027\u80fd\u65b9\u9762\u53d1\u6325\u7740\u81f3\u5173\u91cd\u8981\u7684\u4f5c\u7528\u3002\u5b83\u4eec\u53ef\u7528\u4e8e\uff1a<\/p>\n

                  \n
                1. \n

                  \u5b89\u5168\u8bbf\u95ee<\/strong>\uff1a\u4ee3\u7406\u670d\u52a1\u5668\u5145\u5f53\u7528\u6237\u548c\u6258\u7ba1 Jupyter \u670d\u52a1\u5668\u4e4b\u95f4\u7684\u4e2d\u4ecb\uff0c\u589e\u52a0\u4e86\u989d\u5916\u7684\u5b89\u5168\u5c42\u4ee5\u9632\u6b62\u672a\u7ecf\u6388\u6743\u7684\u8bbf\u95ee\u548c\u6f5c\u5728\u7684\u653b\u51fb\u3002<\/p>\n<\/li>\n

                2. \n

                  \u8d1f\u8f7d\u5747\u8861<\/strong>\uff1a\u4ee3\u7406\u670d\u52a1\u5668\u53ef\u4ee5\u5728\u591a\u4e2a\u6258\u7ba1 Jupyter \u5b9e\u4f8b\u4e4b\u95f4\u5206\u914d\u4f20\u5165\u6d41\u91cf\uff0c\u786e\u4fdd\u9ad8\u6548\u7684\u8d44\u6e90\u5229\u7528\u5e76\u63d0\u9ad8\u6027\u80fd\u3002<\/p>\n<\/li>\n

                3. \n

                  \u6d41\u91cf\u8fc7\u6ee4<\/strong>\uff1a\u4ee3\u7406\u670d\u52a1\u5668\u53ef\u4ee5\u8fc7\u6ee4\u4f20\u5165\u8bf7\u6c42\uff0c\u963b\u6b62\u6076\u610f\u6d41\u91cf\u5e76\u786e\u4fdd\u524d\u7aef\u548c\u5185\u6838\u4e4b\u95f4\u7684\u901a\u4fe1\u987a\u7545\u53ef\u9760\u3002<\/p>\n<\/li>\n<\/ol>\n

                  \u76f8\u5173\u94fe\u63a5<\/h2>\n

                  \u6709\u5173\u6258\u7ba1 Jupyter \u7684\u66f4\u591a\u4fe1\u606f\uff0c\u60a8\u53ef\u4ee5\u6d4f\u89c8\u4ee5\u4e0b\u94fe\u63a5\uff1a<\/p>\n

                    \n
                  1. Jupyter \u9879\u76ee\u7f51\u7ad9<\/a><\/li>\n
                  2. Jupyter \u6587\u6863<\/a><\/li>\n
                  3. Jupyter \u7b14\u8bb0\u672c\u793a\u4f8b<\/a><\/li>\n<\/ol>","protected":false},"featured_media":468562,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-477479","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about Hosted Jupyter: Empowering Collaborative Data Science<\/mark>","faq_items":[{"question":"What is Hosted Jupyter?","answer":"

                    Hosted Jupyter is an innovative web-based platform that allows users to create interactive notebooks containing live code, visualizations, and text. It supports multiple programming languages, making it a powerful tool for data analysis and collaborative research.<\/p>"},{"question":"Who developed Hosted Jupyter and when was it introduced?","answer":"

                    Hosted Jupyter was originally developed by a team of developers led by Fernando P\u00e9rez and Brian Granger. It was first introduced in 2014 as an evolution of the IPython project.<\/p>"},{"question":"How does Hosted Jupyter work?","answer":"

                    When you access Hosted Jupyter through your web browser, the frontend interface allows you to create and edit notebooks. These notebooks are stored on the server, and the code you input is executed by the kernel. The results are then sent back to the frontend for display, facilitating an interactive computing experience.<\/p>"},{"question":"What are the key features of Hosted Jupyter?","answer":"

                    Hosted Jupyter offers interactive computing, data visualization, code sharing, collaboration, and support for multiple programming languages. Its extensibility allows for the integration of various extensions and widgets, enhancing functionality and customization.<\/p>"},{"question":"What types of Hosted Jupyter are available?","answer":"

                    There are different types of Hosted Jupyter instances, including public hosted platforms, private hosted solutions, and cloud-based hosting.<\/p>"},{"question":"What are some common use cases for Hosted Jupyter?","answer":"

                    Hosted Jupyter finds applications in data analysis, research, data visualization, prototyping, testing, and interactive teaching.<\/p>"},{"question":"What challenges might users face while using Hosted Jupyter?","answer":"

                    Users may encounter challenges related to resource-intensive computations, security concerns in shared hosting environments, and managing package versions.<\/p>"},{"question":"How can these challenges be addressed?","answer":"

                    Resource optimization, implementing security measures, and using containerization technologies like Docker can address these challenges effectively.<\/p>"},{"question":"What are the future perspectives for Hosted Jupyter?","answer":"

                    The future of Hosted Jupyter includes improved performance, AI-powered assistance, enhanced collaboration features, and expanded language support.<\/p>"},{"question":"How can proxy servers be associated with Hosted Jupyter?","answer":"

                    Proxy servers can enhance the security and performance of Hosted Jupyter by acting as intermediaries, providing load balancing, and filtering incoming traffic.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/cn\/wp-json\/wp\/v2\/wiki\/477479","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oneproxy.pro\/cn\/wp-json\/wp\/v2\/wiki"}],"about":[{"href":"https:\/\/oneproxy.pro\/cn\/wp-json\/wp\/v2\/types\/wiki"}],"version-history":[{"count":0,"href":"https:\/\/oneproxy.pro\/cn\/wp-json\/wp\/v2\/wiki\/477479\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/cn\/wp-json\/wp\/v2\/media\/468562"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/cn\/wp-json\/wp\/v2\/media?parent=477479"}],"curies":[{"name":"\u53ef\u6e7f\u6027\u7c89\u5242","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}